Unsupervised multimodal fusion of in-process sensor data for advanced manufacturing process monitoring

McKinney, Matthew; Garland, Anthony; Cillessen, Dale; Adamczyk, Jesse; Bolintineanu, Dan; Heiden, Michael; Fowler, Elliott; Boyce, Brad L.

doi:10.1016/j.jmsy.2024.12.003

Title: Unsupervised multimodal fusion of in-process sensor data for advanced manufacturing process monitoring

Journal Article · 01 February 2025 · Journal of Manufacturing Systems

DOI: https://doi.org/10.1016/j.jmsy.2024.12.003 · OSTI ID:2481611

McKinney, Matthew; Garland, Anthony; Cillessen, Dale; Adamczyk, Jesse; Bolintineanu, Dan; Heiden, Michael; Fowler, Elliott; Boyce, Brad L.

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Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: NA0003525

OSTI ID:: 2481611

Journal Information:: Journal of Manufacturing Systems, Journal Name: Journal of Manufacturing Systems Journal Issue: C Vol. 78; ISSN 0278-6125

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (32)

Applications of machine learning in metal powder-bed fusion in-process monitoring and control: status and challenges Zhang, Yingjie; Yan, Wentao Journal of Intelligent Manufacturing, Vol. 34, Issue 6 https://doi.org/10.1007/s10845-022-01972-7	journal	June 2022
Monitoring and control the Wire Arc Additive Manufacturing process using artificial intelligence techniques: a review Mattera, Giulio; Nele, Luigi; Paolella, Davide Journal of Intelligent Manufacturing, Vol. 35, Issue 2 https://doi.org/10.1007/s10845-023-02085-5	journal	February 2023
Intelligent Defect Detection Method for Additive Manufactured Lattice Structures Based on a Modified YOLOv3 Model Zhang, Zhiwei; Zhang, Yuyan; Wen, Yintang Journal of Nondestructive Evaluation, Vol. 41, Issue 1 https://doi.org/10.1007/s10921-021-00835-0	journal	November 2021
Selective laser sintering: A qualitative and objective approach Kumar, Sanjay JOM, Vol. 55, Issue 10 https://doi.org/10.1007/s11837-003-0175-y	journal	October 2003
Overview of Materials Qualification Needs for Metal Additive Manufacturing Seifi, Mohsen; Salem, Ayman; Beuth, Jack JOM, Vol. 68, Issue 3 https://doi.org/10.1007/s11837-015-1810-0	journal	January 2016
Optical process monitoring for Laser-Powder Bed Fusion (L-PBF) Zouhri, W.; Dantan, J. Y.; Häfner, B. CIRP Journal of Manufacturing Science and Technology, Vol. 31 https://doi.org/10.1016/j.cirpj.2020.09.001	journal	November 2020
Deep reinforcement learning for the rapid on-demand design of mechanical metamaterials with targeted nonlinear deformation responses Brown, Nathan K.; Garland, Anthony P.; Fadel, Georges M. Engineering Applications of Artificial Intelligence, Vol. 126 https://doi.org/10.1016/j.engappai.2023.106998	journal	November 2023
Porosity prediction: Supervised-learning of thermal history for direct laser deposition Khanzadeh, Mojtaba; Chowdhury, Sudipta; Marufuzzaman, Mohammad Journal of Manufacturing Systems, Vol. 47 https://doi.org/10.1016/j.jmsy.2018.04.001	journal	April 2018
From in-situ monitoring toward high-throughput process control: cost-driven decision-making framework for laser-based additive manufacturing Jafari-Marandi, Ruholla; Khanzadeh, Mojtaba; Tian, Wenmeng Journal of Manufacturing Systems, Vol. 51 https://doi.org/10.1016/j.jmsy.2019.02.005	journal	April 2019
Toward in-situ flaw detection in laser powder bed fusion additive manufacturing through layerwise imagery and machine learning Snow, Zackary; Diehl, Brett; Reutzel, Edward W. Journal of Manufacturing Systems, Vol. 59 https://doi.org/10.1016/j.jmsy.2021.01.008	journal	April 2021
An augmented surprise-guided sequential learning framework for predicting the melt pool geometry Raihan, Ahmed Shoyeb; Khosravi, Hamed; Bhuiyan, Tanveer Hossain Journal of Manufacturing Systems, Vol. 75 https://doi.org/10.1016/j.jmsy.2024.05.023	journal	August 2024
Review of in-situ process monitoring and in-situ metrology for metal additive manufacturing Everton, Sarah K.; Hirsch, Matthias; Stravroulakis, Petros Materials & Design, Vol. 95 https://doi.org/10.1016/j.matdes.2016.01.099	journal	April 2016
Extraction and evaluation of melt pool, plume and spatter information for powder-bed fusion AM process monitoring Zhang, Yingjie; Hong, Geok Soon; Ye, Dongsen Materials & Design, Vol. 156 https://doi.org/10.1016/j.matdes.2018.07.002	journal	October 2018
Pragmatic generative optimization of novel structural lattice metamaterials with machine learning Garland, Anthony P.; White, Benjamin C.; Jensen, Scott C. Materials & Design, Vol. 203 https://doi.org/10.1016/j.matdes.2021.109632	journal	May 2021
A scalable digital platform for the use of digital twins in additive manufacturing Scime, Luke; Singh, Alka; Paquit, Vincent Manufacturing Letters, Vol. 31 https://doi.org/10.1016/j.mfglet.2021.05.007	journal	January 2022
A photoacoustic imaging method for in-situ monitoring of laser assisted ceramic additive manufacturing Cheng, Baokai; Lei, Jincheng; Xiao, Hai Optics & Laser Technology, Vol. 115 https://doi.org/10.1016/j.optlastec.2019.02.055	journal	July 2019
Data fusion methods for statistical process monitoring and quality characterization in metal additive manufacturing Grasso, Marco; Gallina, Francesco; Colosimo, Bianca Maria Procedia CIRP, Vol. 75 https://doi.org/10.1016/j.procir.2018.04.045	journal	January 2018
Additive manufacturing: Toward holistic design Jared, Bradley H.; Aguilo, Miguel A.; Beghini, Lauren L. Scripta Materialia, Vol. 135 https://doi.org/10.1016/j.scriptamat.2017.02.029	journal	July 2017
Multisensor Fusion-Based Digital twin in Additive Manufacturing for In-Situ Quality Monitoring and Defect Correction Chen, Lequn; Yao, Xiling; Liu, Kui Proceedings of the Design Society, Vol. 3 https://doi.org/10.1017/pds.2023.276	journal	June 2023
Direct mechanistic connection between acoustic signals and melt pool morphology during laser powder bed fusion Sun, Yuchen; Gorgannejad, Sanam; Martin, Aiden Applied Physics Letters, Vol. 125, Issue 3 https://doi.org/10.1063/5.0205663	journal	July 2024
In-process quality improvement: Concepts, methodologies, and applications Shi, Jianjun IISE Transactions, Vol. 55, Issue 1 https://doi.org/10.1080/24725854.2022.2059725	journal	May 2022
Learning Cross-Modal Retrieval with Noisy Labels Hu, Peng; Peng, Xi; Zhu, Hongyuan 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR46437.2021.00536	conference	June 2021
A ConvNet for the 2020s Liu, Zhuang; Mao, Hanzi; Wu, Chao-Yuan 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR52688.2022.01167	conference	June 2022
Towards Total Recall in Industrial Anomaly Detection Roth, Karsten; Pemula, Latha; Zepeda, Joaquin 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR52688.2022.01392	conference	June 2022
ImageBind One Embedding Space to Bind Them All Girdhar, Rohit; El-Nouby, Alaaeldin; Liu, Zhuang 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR52729.2023.01457	conference	June 2023
In-Process Monitoring of Selective Laser Melting: Spatial Detection of Defects Via Image Data Analysis Grasso, Marco; Laguzza, Vittorio; Semeraro, Quirico Journal of Manufacturing Science and Engineering, Vol. 139, Issue 5 https://doi.org/10.1115/1.4034715	journal	November 2016
Super-convergence: very fast training of neural networks using large learning rates Smith, Leslie N.; Topin, Nicholay Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications https://doi.org/10.1117/12.2520589	conference	May 2019
Material identification and segmentation using deep learning for laser powder bed fusion Narayanan, Barath Narayanan; Beigh, Kelly; Duning, Solomon Applications of Machine Learning 2020 https://doi.org/10.1117/12.2567007	conference	August 2020
Thermopore: Predicting Part Porosity Based on Thermal Images Using Deep Learning Pak, Peter; Ogoke, Odinakachukwu Francis; Polonsky, Andrew https://doi.org/10.2139/ssrn.4836563	preprint	May 2024
Monitoring of Laser Powder Bed Fusion by Acoustic Emission: Investigation of Single Tracks and Layers Kouprianoff, D.; Yadroitsava, I.; du Plessis, A. Frontiers in Mechanical Engineering, Vol. 7 https://doi.org/10.3389/fmech.2021.678076	journal	June 2021
Review: The Impact of Metal Additive Manufacturing on the Aerospace Industry Mohd Yusuf, Shahir; Cutler, Samuel; Gao, Nong Metals, Vol. 9, Issue 12 https://doi.org/10.3390/met9121286	journal	November 2019
High-Performance Defect Detection Methods for Real-Time Monitoring of Ceramic Additive Manufacturing Process Based on Small-Scale Datasets Jia, Xinjian; Li, Shan; Wang, Tongcai Processes, Vol. 12, Issue 4 https://doi.org/10.3390/pr12040633	journal	March 2024

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